Data-driven identification of heart failure disease states and progression pathways using electronic health records.

Heart failure (HF) is a leading cause of morbidity, healthcare costs, and mortality. Guideline based segmentation of HF into distinct subtypes is coarse and unlikely to reflect the heterogeneity of etiologies and disease trajectories of patients. While analyses of electronic health records show promise in expanding our understanding of complex syndromes like HF in an evidence-driven way, limitations in data quality have presented challenges for large-scale EHR-based insight generation and decision-making.

Tumor Suppressor DAPK1 Catalyzes Adhesion Assembly on Rigid but Anoikis on Soft Matrices.

Cancer cells normally grow on soft surfaces due to impaired mechanosensing of the extracellular matrix rigidity. Upon restoration of proper mechanosensing, cancer cells undergo apoptosis on soft surfaces (anoikis) like most normal cells. However, the link between mechanosensing and activation of anoikis is not clear.

Development of a Method for Clinical Evaluation of Artificial Intelligence-Based Digital Wound Assessment Tools.

Importance: Accurate assessment of wound area and percentage of granulation tissue (PGT) are important for optimizing wound care and healing outcomes. Artificial intelligence (AI)-based wound assessment tools have the potential to improve the accuracy and consistency of wound area and PGT measurement, while improving efficiency of wound care workflows.

Objective: To develop a quantitative and qualitative method to evaluate AI-based wound assessment tools compared with expert human assessments.

Multiscale classification of heart failure phenotypes by unsupervised clustering of unstructured electronic medical record data.

As a leading cause of death and morbidity, heart failure (HF) is responsible for a large portion of healthcare and disability costs worldwide. Current approaches to define specific HF subpopulations may fail to account for the diversity of etiologies, comorbidities, and factors driving disease progression, and therefore have limited value for clinical decision making and development of novel therapies. Here we present a novel and data-driven approach to understand and characterize the real-world manifestation of HF by clustering disease and symptom-related clinical concepts (complaints) captured from unstructured electronic health record clinical notes.

Large and reversible myosin-dependent forces in rigidity sensing.

Cells sense the rigidity of their environment through localized pinching, which occurs when myosin molecular motors generate contractions within actin filaments anchoring the cell to its surroundings. We present high-resolution experiments performed on these elementary contractile units in cells. Our experimental results challenge the current understanding of molecular motor force generation.

The Future of Data-Driven Wound Care.

Care for patients with chronic wounds can be complex, and the chances of poor outcomes are high if wound care is not optimized through evidence-based protocols. Tracking and managing every variable and comorbidity in patients with wounds is difficult despite the increasing use of wound-specific electronic medical records. Harnessing the power of big data analytics to help nurses and physicians provide optimized care based on the care provided to millions of patients can result in better outcomes.

Force-Induced Calpain Cleavage of Talin Is Critical for Growth, Adhesion Development, and Rigidity Sensing.

Cell growth depends upon formation of cell-matrix adhesions, but mechanisms detailing the transmission of signals from adhesions to control proliferation are still lacking. Here, we find that the scaffold protein talin undergoes force-induced cleavage in early adhesions to produce the talin rod fragment that is needed for cell cycle progression. Expression of noncleavable talin blocks cell growth, adhesion maturation, proper mechanosensing, and the related property of EGF activation of motility.

EGFR and HER2 activate rigidity sensing only on rigid matrices.

Epidermal growth factor receptor (EGFR) interacts with integrins during cell spreading and motility, but little is known about the role of EGFR in these mechanosensing processes. Here we show, using two different cell lines, that in serum- and EGF-free conditions, EGFR or HER2 activity increase spreading and rigidity-sensing contractions on rigid, but not soft, substrates. Contractions peak after 15-20 min, but diminish by tenfold after 4 h.

Cellular response to substrate rigidity is governed by either stress or strain.

Cells sense the rigidity of their substrate; however, little is known about the physical variables that determine their response to this rigidity. Here, we report traction stress measurements carried out using fibroblasts on polyacrylamide gels with Young's moduli ranging from 6 to 110 kPa. We prepared the substrates by employing a modified method that involves N-acryloyl-6-aminocaproic acid (ACA).